Triple

T1778987
Position Surface form Disambiguated ID Type / Status
Subject Tessa Thompson E39245 entity
Predicate givenName P17 FINISHED
Object Tessa
Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
 E213395 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tessa | Statement: [Tessa Thompson, givenName, Tessa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tessa
Context triple: [Tessa Thompson, givenName, Tessa]
  • A. Chloe
    Chloe is the birth name of Nobel Prize–winning American novelist Toni Morrison, renowned for her powerful explorations of African American life and history.
  • B. Chloe
    Chloe is an epithet of the Greek goddess Demeter, highlighting her aspect as the bringer of new green growth and flourishing vegetation.
  • C. Zoe
    Zoe is a feminine given name of Greek origin meaning "life," commonly used in many English-speaking and European countries.
  • D. Tanya
    Tanya is the foundational Chabad-Lubavitch Hasidic work by Rabbi Shneur Zalman of Liadi, presenting a systematic approach to Jewish mysticism, psychology, and spiritual self-improvement.
  • E. Teressa
    Teressa is a Nicobarese language variety spoken by the indigenous community on Teressa Island in India’s Nicobar archipelago.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tessa
Triple: [Tessa Thompson, givenName, Tessa]
Generated description
Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tessa
Target entity description: Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • A. Chloe
    Chloe is the birth name of Nobel Prize–winning American novelist Toni Morrison, renowned for her powerful explorations of African American life and history.
  • B. Chloe
    Chloe is an epithet of the Greek goddess Demeter, highlighting her aspect as the bringer of new green growth and flourishing vegetation.
  • C. Zoe
    Zoe is a feminine given name of Greek origin meaning "life," commonly used in many English-speaking and European countries.
  • D. Tanya
    Tanya is the foundational Chabad-Lubavitch Hasidic work by Rabbi Shneur Zalman of Liadi, presenting a systematic approach to Jewish mysticism, psychology, and spiritual self-improvement.
  • E. Teressa
    Teressa is a Nicobarese language variety spoken by the indigenous community on Teressa Island in India’s Nicobar archipelago.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64ba92a48190b69da748dfbfc53c completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaceae088190a5ee93e6b46360cc completed March 8, 2026, 9:31 p.m.
NEDg Description generation batch_69adeb8a0a64819087e4505089e93093 completed March 8, 2026, 9:35 p.m.
NED2 Entity disambiguation (via description) batch_69adec6fcaac8190b43d0cd1aa613c95 completed March 8, 2026, 9:38 p.m.
Created at: March 4, 2026, 7:31 p.m.